Method for detecting mobile objects using passive submarine buoys

ABSTRACT

The invention is a process relating to the processing of the signals sent by passive buoys dropped from an aircraft so as to compile EGP (Energy Geographic Plot) maps.  
     The process is split into three steps: the first makes it possible to produce an EGP map of the x,y positions of the noise sources, the second makes it possible to associate the velocities V x , V y  with certain designated positions and the third makes it possible to eliminate the noise sources regarded as hampering the readability of the maps.

[0001] The present invention concerns systems which make it possible tolocate and identify underwater objects acoustically with the aid of acollection of passive underwater buoys.

[0002] It relates more particularly to the means for processing thereception signals of these buoys, which are generally transmitted byradio to a processing base usually situated on board an aircraft.

PRIOR ART

[0003] It is known practice for objects submerged under the sea,submarines for example, to be located via their noise by droppingpassive acoustic buoys from an aircraft equipped for this purpose. Thus,in the French Patent filed under No. 9203005, on Mar. 13, 1992 in thename of THOMSON-CSF and published on Sep. 17, 1993 under No. 2 688 595,there is described a system for detection by means of an array ofpassive underwater buoys of the type known as “DIFAR” (DirectionalFrequency Analysis and Recording) and more particularly a processingprocess making it possible to locate several noise sources. This processis incomplete and does not in particular make it possible to determinethe velocities of the noise sources. In this sense, the process does notmake it possible to map a complete “EGP” map, EGP being the abbreviationstanding for Energy Geographic Plot.

SUMMARY OF THE INVENTION

[0004] To complete this process, the invention proposes a process fordetecting mobile objects by means of passive underwater buoys making itpossible to obtain so-called EGP maps, each buoy allowing the formationof N_(v) directive pathways, chiefly characterized in that the signalsfrom the buoys are processed in three steps:

[0005] a first step (90-102) making it possible to obtain an EGP map ofthe x,y positions of the objects,

[0006] a second step (110-120) making it possible to obtain an EGP mapof the velocities Vx,Vy as well as an estimated spectrum for eacharbitrary position x,y of the EGP map of the positions, these mapsexhibiting the Doppler ambiguity loci,

[0007] a third step (140-144) allowing the elimination from the maps ofthe objects regarded as strong sources of noise.

[0008] According to another characteristic, the first step consists inproducing an EGP map of the positions by an iteration of operations ofdetection on the set of the frequency channels constituting the analyzedband, each detection being obtained by comparison of the generalizedlikelihood ratio with a threshold, and with each detection is associateda decisional summary containing the coordinates x,y, the signal-to-noiseratio SNR, the presence probability distribution for the maximum,representing a possible target or noise source, and, for each buoy, itsrelative contribution to the maximum.

[0009] According to another characteristic, the second step consists,for each detection on the EGP map of the positions emanating from thefirst step, in selecting the frequency channels that have participatedin the detection by using the “presence probability distribution” datum,in merging the “SNR” data which correspond to these channels giving aglobal spectrum, in deducing the object's spectra seen by each buoy byusing the “relative contribution” datum, in grouping together thespectrum-to-spectrum homologous frequencies, in calculating the averageof these homologous frequencies thus giving a spectrum representing thespectral profile of the noise source supposedly placed at the maximum,in calculating the differential Dopplers between the buoys on the basisof this spectrum, making it possible to obtain the velocities V_(x),V_(y) corresponding to this detection, in iterating the procedure forall the detections and, at the end of the analyzed band in associatingthe velocities V_(x), V_(y) with the coordinates x,y so as to obtain anEGP map of the velocities.

[0010] According to another characteristic, the third step consists, foreach noise source to be eliminated, which noise source is set on the EGPmap of the positions, in again selecting the frequency channels, inestimating the power of the noise source so as to calculate thetheoretical level of the signal originating from the noise source and insubtracting it from the actual level, in iterating this subtraction foreach frequency channel so as, at the end of the analyzed band, torecommence the previous steps 1 and 2.

[0011] According to another characteristic, steps 1 and 2 are merged byiterating over the frequency channels, before performing the detection;the calculation of the differential Dopplers being taken into account inthe detection criterion.

BRIEF DESCRIPTION OF FIGURES

[0012] Other features and advantages of the invention will becomeclearly apparent in the following description, presented by way ofnonlimiting example with regard to the appended figures which represent:

[0013]FIG. 1, a diagram of the process according to the invention;

[0014]FIG. 2, a variant of this process.

DETAILED DESCRIPTION

[0015] cording to the invention, the process chiefly comprises:

[0016] a data merge carried out over the collection of buoys by means ofthe likelihood ratio of the spectral observations,

[0017] the use of differential Dopplers after estimation of thefrequencies emitted,

[0018] the canceling out of noise sources integrated into the previousspatial merge and Doppler processings.

[0019]FIG. 1 represents the processing of the signals provided by theDIFAR buoys and culminating, upon compilation of an EGP map of thepositions and for each noise source, designated automatically or by theoperator, in an EGP map of the velocities.

[0020] The input data consist of the normalized spectra (x/estimatedmean) S_(i,b)(f) with

[0021] 1≦i≦N_(v) (number of pathways)

[0022] 1≦b≦N (number of buoys).

[0023] For each buoy, a sufficient number of pathways, for exampleN_(v)≧6, is formed so that the loss of detection due to the differencebetween the pointing direction and the bearing of the source isnegligible.

[0024] According to the invention, the processing is performed in threesteps:

[0025] step 1: determination of the positions of the noise sources;

[0026] step 2: determination of the velocity and of the spectrum of afew noise sources designated automatically or by the operator;

[0027] step 3: elimination of the strong sources of noise.

[0028] In step 1, for each frequency channel of the spectra, onecommences by eliminating the spectral components of the buoys whosepower level is insufficient in an operation 99. Thus, in the presence ofa “strong spectral line”, the buoys not receiving this spectral line onaccount of the Doppler effect are discarded so as not to bias theestimation of the position of the noise source by the maximum likelihoodmethod. In the absence of any strong spectral line, the contributionsfrom all the buoys are retained. To do this, the power of the signalreceived for a frequency channel is compared with a normalized thresholdequal to the sum of the mean of the spectral noise and of the product ofthe test threshold chosen times the standard deviation of the spectralnoise: a typical value of the test threshold is 4, the standarddeviation equals 0.5227I {square root}{square root over (N_(SI))}.(N_(si): number of integrated spectra) and the mean power of the noiseequals 1.

[0029] One thus obtains a collection of spectral components, denotedR_(i,b) (f) with 1≦b≦M, M being less than or equal to N if certain buoysdo not overstep the threshold. This collection of spectral componentsconstitutes the observation vector X for the relevant frequency channel.

[0030] Thereafter, in an operation 100, the square root of thegeneralized likelihood ratio of the observations is calculated, thusforming an EGPf map of the spectral channel f:

[0031] The expression calculated is:${I\left( {x,y} \right)} = {\frac{1}{\sqrt{2}}\frac{{\left( {X - \Gamma} \right)^{T}R^{- 1}S}}{\sqrt{S^{T}R^{- 1}S}}}$

[0032] in which:

[0033] X: vector of dimension N_(v).M of the spectral components R_(i,b)

[0034] Γ: vector giving the mean level of the noise on each pathway ofeach buoy

[0035] C⁻¹: inverse matrix of the covariance of the observation for asingle buoy such that: R¹ = c₁¹⋯ _(c_(i)¹⋯_(c_(N)¹⋯))

[0036] R⁻¹ inverse matrix of the covariance of the observation overN_(v) buoys.

[0037] S: vector of the values representing sensitivity of the variouspathways of the various buoys for a target situated at a geographicalposition (x,y).

[0038] Next, in an operation 101, the detection of a target on thesingle-channel EGPf map is firstly performed and a “decisional summary”is thereafter compiled in respect of the latter map.

[0039] Detection consists:

[0040] in fixing a constant false alarm probability at each point of theEGP_(f) map,

[0041] in calculating a threshold I₀, independent of the position of themaximum, equal to the sum of the mean of the noise of the map and of theproduct of the test threshold times by the standard deviation of thenoise of the map.

[0042] in searching for the maxima by thresholding with I₀.

[0043] The decisional summary associated with each detection consists ofthe following elements:

[0044] the coordinates x,y

[0045] the signal-to-noise ratio SNR=(amplitude/standard deviation ofnoise )²

[0046] the presence probability distribution for the maximum, that is tosay the 0.95 probability boundary determined by the overstepping orotherwise of the threshold equal to max−k/max , being a coefficientlying between 1.5 and 3 so as to take account of the discrepancies withrespect to the expected statistics, the location of the maximumapproximately following to a Woodward type procedure.

[0047] the relative contributions of each buoy, i.e. for a buoy theratio between the level of the pathway pointing nearest to the maximumand the sum of these levels for all the buoys.

[0048] The processing corresponding to the operations 99, 100, 101 isrepeated for all the frequency channels of the analyzed band, which maybe of arbitrary width.

[0049] At the end of this step 1, by merging of the coordinates x,y ofthe decisional summaries, one obtains the global EGP map of thepositions (102) of the objects thus located.

[0050] In step 2, one commences by searching, in an operation 110, overthe collection, or over a part, of the maxima of the overall EGP map ofthe positions, for the frequency channels that have participated in theconstruction of each maximum. To do this, the datum relating to thepresence probability distribution for the decisional summaries is used.If the position of the maximum is contained in the 0.95 probabilityboundary. The frequency channels indicate the various emissionfrequencies of the target that are observed by one of any of the buoysof the array. The set of channels participating defines a globalspectrum of the object, all buoys included, such that Sg(f)=SNR(f), thevalues SNR(F) being chosen from the decisional summaries.

[0051] Next, in an operation 111, with the values of the relativecontributions of each buoy, chosen from the decisional summaries, theobject's spectra seen by each buoy are determined from S_(g)(f), i.e.:

S _(b)(f)=S _(g)(f)×contribution (b, f)

[0052] A grouping/pairing, from buoy spectrum to buoy spectrum, of thehomologous frequencies that are shifted only by the Doppler effect iscarried out thereafter. This is achieved by correlation of portions ofthe spectra S_(b)(f) of the EGP maximum (and hence of the target). Onethus obtains the Doppler shifts observed, for one and the same spectralline, for one buoy to the next, as well as by averaging an estimate ofthe frequencies emitted by the target S_(c)(f).

[0053] The processing is continued by performing, in an operation 112,for each of the spectral lines or of the portions of strong level of thespectrum S_(c)(f), the calculation of the differential Dopplers(frequency differences) observed between the buoys, making it possibleto obtain the velocities V_(x),V_(y) of the object.

[0054] The Doppler ambiguity loci associated with each of the observedfrequency differences are determined thereafter. These loci are bandsparallel to the bisector of the angle formed by the two straight linesjoining the position of the object to the buoys b_(i), b_(j). The widthof these bands depends on the fineness of the frequency channels of thespectral analysis. Advantageously, each band is endowed with a maximumlevel equal to S_(bi)(f)×S_(bj)(f).

[0055] The processing corresponding to the operations 110, 111 and 112is repeated for all the maxima selected on the EGP map. At the end ofthis step 2, by associating the velocities V_(x),V_(y) with thecoordinates x,y of the maxima and by summing the Doppler ambiguity loci,one obtains the EGP map of the velocities of the objects located, withthe Doppler ambiguity loci.

[0056] According to the invention, the process integrates theelimination from the EGP maps of the objects which are strong “sourcesof noise”. The processing forms step 3. The latter consists of thefollowing substeps:

[0057] designation in an operation 140 by the operator of thecoordinates x,y of the noise sources to be eliminated on the EGP map ofthe positions,

[0058] for each noise source in an operation 141, iteration of thescheme which corresponds to the operation 110,

[0059] for each frequency channel, in an operation 142 estimation of thepower of the noise source equal to $\frac{\sqrt{SNR}}{S^{T}R^{1}S}$

[0060] where S is the vector representing the sensitivity of thepathways of the buoys for the position occupied by the noise source, SNRbeing a value preserved in the decisional summary,

[0061] then, having regard to the estimated power and to the coordinatesx,y of the noise source, in an operation 143 we calculate for each ofthe pathways of each of the buoys, the theoretical signal leveloriginating from the noise source, providing a vector A of the expectedspectral values,

[0062] finally for a frequency channel, in an operation 144 calculationof the vector X-A which then replaces X.

[0063] The processing corresponding to operations 142, 143, 144 isrepeated for all the frequency channels that have participated in theconstruction of the signal of the noise source. Once the frequency bandhas been explored, the processing of steps 1 and 2 is applied to the newobservations until there are no longer any noise sources to beeliminated.

[0064] According to a variant, steps 1 and 2 may be reduced to a singlestep along with an increase in the calculational burden. In thisvariant, the frequency merge is done before the detection and thedifferential Dopplers are taken into account in the detection criterion.FIG. 2 represents the flowchart of the variant which replaces in FIG. 1the operations from 99 to 130.

[0065] In a spectral band Δf at most a few tens of Hz wide, and slightlywider than the maximum expected Doppler shifts:

[0066] for each analysis frequency f belonging to the previous band Δf,

[0067] for each position (x,y) in the EGP map,

[0068] for a hypothesis (v_(x),v_(y)) of possible velocity of the noisesource at this position (x,y), and all these hypotheses {f, (x,y),(v_(x),v_(y))} will be scanned subsequently.

[0069] The Doppler shifts that ought to be obtained on the various buoysof the array are calculated and an observation vector of the buoysignals is reconstructed by selecting for each buoy the outputs of thespectral channels whose frequency is the noise source's supposedemission frequency to which the appropriate Doppler shift is added.Hence, an observation vector is formed here after a scheme carrying outa “spectral focusing” of sorts.

[0070] Once the observation vector has been obtained after spectralfocusing, the EGP formation procedure is applied,${I\left( {x,y} \right)} = {\frac{1}{\sqrt{2}}\frac{{\left( {X - \Gamma} \right)^{T}R^{- 1}S}}{\sqrt{S^{T}R^{- 1}S}}}$

[0071] as described previously in step 1, thus obtaining the value ofthe EGP map for the relevant hypotheses in terms of emission frequency,position and velocity of the noise source.

[0072] The result of the exploration of the scanned hypotheses iseffected by the process known by the expression “peak-picking”, whichdesignates an operation of selecting a maximum from a collection ofnumbers, and two results are formed, one giving an EGP map of thepositions (“peak-picking” as regards the frequency and velocityhypotheses), the other giving an EGP map of the velocities(“peak-picking” as regards the frequency and position hypotheses). Thecomparison of the two EGP maps, position and velocity, also makes itpossible, by charting the various noise sources, to correctly associateposition, velocity and frequency for one and the same noise source.

[0073] On the other hand, to explore a band B a few thousand Hz wide,possibly containing more than one hundred subbands of width Δf, whichsubbands are completely independent of one another a priori, the variantproposes that the following method be applied:

[0074] chopping of B into half-overlapping subbands Δf,

[0075] formation of the multi-hypothesis EGP images peak-picked, interms of position and velocity (as in the previous paragraph) for eachof the subbands,

[0076] detection of targets, if any, in the EGP images obtained oncompletion of the processing of each subband, as described at 101 instep 1; two decisional summaries are then obtained for each subband,

[0077] merging of the detection results by using the decisionalsummaries of the detection in each subband, as described at 102 in step1,

[0078] representation of the two merged images of position and ofvelocity, by charting the various noise sources in such a way as to beable to associate position, velocity and frequency for one and the samenoise source.

[0079] It will be noted that with this variant, it is possible toextract more than one target during the operation of detecting targets,if any, in the EGP images obtained on completion of the processing ofeach subband.

[0080] The subtraction of strong sources of noise is also done with thisvariant according to a similar scheme to that described for the initialEGP method.

1. A process for detecting mobile objects by means of passive underwaterbuoys making it possible to obtain so-called EGP maps, each buoyallowing the formation of N_(v) directive pathways, wherein the signalsfrom the buoys are processed in three steps: a first step (99-102)making it possible to obtain an EGP map of the x,y positions of theobjects, a second step (110-120) making it possible to obtain an EGP mapof the velocities Vx,Vy as well as an estimated spectrum for eacharbitrary position x,y of the EGP map of the positions, maps exhibitingthe Doppler ambiguity loci, a third step (140-144) allowing theelimination from the maps of the objects regarded as strong sources ofnoise.
 2. The process as claimed in claim 1, wherein the first stepconsists in producing an EGP map of the positions by an iteration ofoperations of detection on the set of the frequency channelsconstituting the analyzed band, each detection being obtained bycomparison of the generalized likelihood ratio with a threshold, and inthat with each detection is associated a decisional summary containingthe coordinates x,y, the signal-to-noise ratio SNR, the presenceprobability distribution for the maximum representing a possible targetor noise source, and, for each buoy, its relative contribution to themaximum.
 3. The process as claimed in either of claims 1, and 2, whereinthe second step consists, for each detection on the EGP map of thepositions emanating from the first step, in selecting the frequencychannels that have participated in the detection by using the “presenceprobability distribution” datum, in merging the “SNR” data whichcorrespond to these channels giving a global spectrum, in deducing theobject's spectra seen by each buoy by using the “relative contribution”datum, in grouping together the spectrum-to-spectrum homologousfrequencies, in calculating the average of these homologous frequenciesthus giving a spectrum representing the spectral profile of the noisesource supposedly placed at the maximum, in calculating the differentialDopplers between the buoys on the basis of this spectrum, making itpossible to obtain the velocities V_(x),V_(y) corresponding to thisdetection, in iterating the procedure for all the detections and, at theend of the analyzed band in associating the velocities V_(x),V_(y) withthe coordinates x,y so as to obtain an EGP map of the velocities.
 4. Theprocess as claimed in claim 1, wherein the third step consists, for eachnoise source to be eliminated, which noise source is located on the EGPmap of the positions, in again selecting the frequency channels, inestimating the power of the noise source so as to calculate thetheoretical level of the signal originating from the noise source and insubtracting it from the actual level, in iterating this subtraction foreach frequency channel so as, at the end of the analyzed band, torecommence the previous steps 1 and
 2. 5. The process as claimed inclaim 1, wherein steps 1 and 2 are merged by iterating over thefrequency channels, before performing the detection; the calculation ofthe differential Dopplers being taken into account in the detectioncriterion.